python爬虫之scrapy框架

　　Scrapy是一个为了爬取网站数据，提取结构性数据而编写的应用框架。其可以应用在数据挖掘，信息处理或存储历史数据等一系列的程序中。
其最初是为了页面抓取 (更确切来说, 网络抓取 )所设计的，也可以应用在获取API所返回的数据(例如 Amazon Associates Web Services ) 或者通用的网络爬虫。Scrapy用途广泛，可以用于数据挖掘、监测和自动化测试。

Scrapy 使用了 Twisted异步网络库来处理网络通讯。整体架构大致如下

Scrapy主要包括了以下组件：

引擎(Scrapy)
用来处理整个系统的数据流处理, 触发事务(框架核心)
调度器(Scheduler)
用来接受引擎发过来的请求, 压入队列中, 并在引擎再次请求的时候返回. 可以想像成一个URL（抓取网页的网址或者说是链接）的优先队列, 由它来决定下一个要抓取的网址是什么, 同时去除重复的网址
下载器(Downloader)
用于下载网页内容, 并将网页内容返回给蜘蛛(Scrapy下载器是建立在twisted这个高效的异步模型上的)
爬虫(Spiders)
爬虫是主要干活的, 用于从特定的网页中提取自己需要的信息, 即所谓的实体(Item)。用户也可以从中提取出链接,让Scrapy继续抓取下一个页面
项目管道(Pipeline)
负责处理爬虫从网页中抽取的实体，主要的功能是持久化实体、验证实体的有效性、清除不需要的信息。当页面被爬虫解析后，将被发送到项目管道，并经过几个特定的次序处理数据。
下载器中间件(Downloader Middlewares)
位于Scrapy引擎和下载器之间的框架，主要是处理Scrapy引擎与下载器之间的请求及响应。
爬虫中间件(Spider Middlewares)
介于Scrapy引擎和爬虫之间的框架，主要工作是处理蜘蛛的响应输入和请求输出。
调度中间件(Scheduler Middewares)
介于Scrapy引擎和调度之间的中间件，从Scrapy引擎发送到调度的请求和响应。

Scrapy运行流程大概如下：

1. 引擎从调度器中取出一个链接(URL)用于接下来的抓取
2. 引擎把URL封装成一个请求(Request)传给下载器
3. 下载器把资源下载下来，并封装成应答包(Response)
4. 爬虫解析Response
5. 解析出实体（Item）,则交给实体管道进行进一步的处理
6. 解析出的是链接（URL）,则把URL交给调度器等待抓取

linux系统

pip3 install scrapy

Windows系统

#scrapy 的一些依赖：pywin32、pyOpenSSL、Twisted、lxml 、zope.interface。（安装的时候，注意看报错信息）

#安装wheel
pip3 install wheel-i http://pypi.douban.com/simple --trusted-host pypi.douban.com

#安装这个依赖包，才有安装上Twisted
pip3 install Incremental -i http://pypi.douban.com/simple --trusted-host pypi.douban.com

#再pip3安装Twisted，但是还是安装不成功，会报错。（解决其它依赖问题）
pip3 install Twisted -i http://pypi.douban.com/simple --trusted-host pypi.douban.com

#再进入软件存放目录，再安装就可以成功啦。
pip3 install Twisted-17.1.0-cp35-cp35m-win32.whl

#安装scrapy
pip3 install scrapy -i http://pypi.douban.com/simple --trusted-host pypi.douban.com

#pywin32
下载：https://sourceforge.net/projects/pywin32/files/

检查pywin32是否安装成功。

C:\Users\Administrator>python
Python 3.5.2 (v3.5.2:4def2a2901a5, Jun 25 2016, 22:01:18) [MSC v.1900 32 bit (Intel)] on win32
Type "help", "copyright", "credits" or "license" for more information.>>> import win32api
>>> import win32con
>>> win32api.MessageBox(win32con.NULL, 'Python 你好！', '你好', win32con.MB_OK)

二、基本使用

1. 基本命令

#创建项目
scrapy startproject xiaohuar#进入项目
cd xiaohuar#创建爬虫应用
scrapy genspider xiaohuar xiaohar.com#运行爬虫
scrapy crawl chouti --nolog

2.项目结构以及爬虫应用简介

文件说明：
scrapy.cfg  项目的主配置信息。（真正爬虫相关的配置信息在settings.py文件中）
items.py    设置数据存储模板，用于结构化数据，如：Django的Model
pipelines    数据处理行为，如：一般结构化的数据持久化
settings.py 配置文件，如：递归的层数、并发数，延迟下载等
spiders      爬虫目录，如：创建文件，编写爬虫规则

注意：一般创建爬虫文件时，以网站域名命名

import scrapyclass XiaoHuarSpider(scrapy.spiders.Spider):name = "xiaohuar"                            # 爬虫名称 *****allowed_domains = ["xiaohuar.com"]  # 允许的域名start_urls = ["http://www.xiaohuar.com/hua/",   # 其实URL]def parse(self, response):# 访问起始URL并获取结果后的回调函数爬虫1.py

3、找标签方法

# -*- coding: utf-8 -*-
import scrapy
import sys
import io
from scrapy.http import Request
from scrapy.selector import Selector, HtmlXPathSelector
from ..items import ChoutiItemsys.stdout = io.TextIOWrapper(sys.stdout.buffer,encoding='gb18030')class ChoutiSpider(scrapy.Spider):name = "chouti"allowed_domains = ["chouti.com"]start_urls = ['http://dig.chouti.com/']visited_urls =set()# def start_requests(self):#     for url in self.start_urls:#         yield Request(url,callback=self.parse)def parse(self, response):# content = str(response.body,encoding='utf-8')# 找到文档中所有A标签# hxs = Selector(response=response).xpath('//a') # 标签对象列表# for i in hxs:#     print(i) # 标签对象# 对象转换为字符串# hxs = Selector(response=response).xpath('//div[@id="content-list"]/div[@class="item"]').extract()  # 标签对象列表# hxs = Selector(response=response).xpath('//div[@id="content-list"]/div[@class="item"]')  # 标签对象列表# for obj in hxs:#     a = obj.xpath('.//a[@class="show-content"]/text()').extract_first()#     print(a.strip())# 选择器："""
        //   表示子孙中.//  当前对象的子孙中/    儿子/div 儿子中的div标签/div[@id="i1"]  #儿子中的div标签且id=i1/div[@id="i1"]  #儿子中的div标签且id=i1obj.extract()         # 列表中的每一个对象转换字符串 =》 []obj.extract_first()   # 列表中的每一个对象转换字符串 => 列表第一个元素//div/text()    获取某个标签的文本"""
# 获取当前页的所有页码# hxs = Selector(response=response).xpath('//div[@id="dig_lcpage"]//a/text()')# hxs = Selector(response=response).xpath('//div[@id="dig_lcpage"]//a/@href').extract()# hxs = Selector(response=response).xpath('//a[starts-with(@href, "/all/hot/recent/")]/@href').extract()# responsehxs1 = Selector(response=response).xpath('//div[@id="content-list"]/div[@class="item"]')  # 标签对象列表for obj in hxs1:title = obj.xpath('.//a[@class="show-content"]/text()').extract_first().strip()href =  obj.xpath('.//a[@class="show-content"]/@href').extract_first().strip()item_obj = ChoutiItem(title=title,href=href)# 将item对象传递给pipelineyield item_objhxs2 = Selector(response=response).xpath('//a[re:test(@href, "/all/hot/recent/\d+")]/@href').extract()for url in hxs2:md5_url = self.md5(url)if md5_url in self.visited_urls:passelse:self.visited_urls.add(md5_url)url = "http://dig.chouti.com%s" %url# 将新要访问的url添加到调度器yield Request(url=url,callback=self.parse)# a/@href  获取属性# //a[starts-with(@href, "/all/hot/recent/")]/@href'  已xx开始# //a[re:test(@href, "/all/hot/recent/\d+")]          正则# yield Request(url=url,callback=self.parse)          # 将新要访问的url添加到调度器# 重写start_requests，指定最开始处理请求的方法# def show(self,response):#     print(response.text)def md5(self,url):import hashlibobj = hashlib.md5()obj.update(bytes(url,encoding='utf-8'))return obj.hexdigest()

3. 小试牛刀

import scrapy
from scrapy.selector import HtmlXPathSelector
from scrapy.http.request import Requestclass DigSpider(scrapy.Spider):# 爬虫应用的名称，通过此名称启动爬虫命令name = "dig"# 允许的域名allowed_domains = ["chouti.com"]# 起始URLstart_urls = ['http://dig.chouti.com/',]has_request_set = {}def parse(self, response):print(response.url)hxs = HtmlXPathSelector(response)page_list = hxs.select('//div[@id="dig_lcpage"]//a[re:test(@href, "/all/hot/recent/\d+")]/@href').extract()for page in page_list:page_url = 'http://dig.chouti.com%s' % pagekey = self.md5(page_url)if key in self.has_request_set:passelse:self.has_request_set[key] = page_urlobj = Request(url=page_url, method='GET', callback=self.parse)yield obj@staticmethoddef md5(val):import hashlibha = hashlib.md5()ha.update(bytes(val, encoding='utf-8'))key = ha.hexdigest()return key

执行此爬虫文件，则在终端进入项目目录执行如下命令：

 scrapy crawl dig --nolog

对于上述代码重要之处在于：

Request是一个封装用户请求的类，在回调函数中yield该对象表示继续访问
HtmlXpathSelector用于结构化HTML代码并提供选择器功能

4、选择器

#!/usr/bin/env python
# -*- coding:utf-8 -*-
from scrapy.selector import Selector, HtmlXPathSelector
from scrapy.http import HtmlResponse
html = """<!DOCTYPE html>
<html><head lang="en"><meta charset="UTF-8"><title></title></head><body><ul><li class="item-"><a id='i1' href="link.html">first item</a></li><li class="item-0"><a id='i2' href="llink.html">first item</a></li><li class="item-1"><a href="llink2.html">second item<span>vv</span></a></li></ul><div><a href="llink2.html">second item</a></div></body>
</html>
"""
response = HtmlResponse(url='http://example.com', body=html,encoding='utf-8')
# hxs = HtmlXPathSelector(response)
# print(hxs)
# hxs = Selector(response=response).xpath('//a')  #找到a标签
# print(hxs)
# hxs = Selector(response=response).xpath('//a[2]') #找到列表中的第2个
# print(hxs)
# hxs = Selector(response=response).xpath('//a[@id]') #找到有a标签的属性
# print(hxs)
# hxs = Selector(response=response).xpath('//a[@id="i1"]') #找到ID=他的值
# print(hxs)
# hxs = Selector(response=response).xpath('//a[@href="link.html"][@id="i1"]')
# print(hxs)
# hxs = Selector(response=response).xpath('//a[contains(@href, "link")]')
# print(hxs)
# hxs = Selector(response=response).xpath('//a[starts-with(@href, "link")]')
# print(hxs)
# hxs = Selector(response=response).xpath('//a[re:test(@id, "i\d+")]') #正测表达式
# print(hxs)
# hxs = Selector(response=response).xpath('//a[re:test(@id, "i\d+")]/text()').extract()
# print(hxs)
# hxs = Selector(response=response).xpath('//a[re:test(@id, "i\d+")]/@href').extract()
# print(hxs)
# hxs = Selector(response=response).xpath('/html/body/ul/li/a/@href').extract() 
# print(hxs)
# hxs = Selector(response=response).xpath('//body/ul/li/a/@href').extract_first()
# print(hxs)# ul_list = Selector(response=response).xpath('//body/ul/li')
# for item in ul_list:
#     v = item.xpath('./a/span')
#     # 或
#     # v = item.xpath('a/span')
#     # 或
#     # v = item.xpath('*/a/span')
#     print(v)

示例：自动登陆抽屉并点赞

# -*- coding: utf-8 -*-
import scrapy
from scrapy.selector import HtmlXPathSelector
from scrapy.http.request import Request
from scrapy.http.cookies import CookieJar
from scrapy import FormRequestclass ChouTiSpider(scrapy.Spider):# 爬虫应用的名称，通过此名称启动爬虫命令name = "chouti"# 允许的域名allowed_domains = ["chouti.com"]cookie_dict = {}has_request_set = {}def start_requests(self):url = 'http://dig.chouti.com/'# return [Request(url=url, callback=self.login)]yield Request(url=url, callback=self.login)def login(self, response):cookie_jar = CookieJar()cookie_jar.extract_cookies(response, response.request)for k, v in cookie_jar._cookies.items():for i, j in v.items():for m, n in j.items():self.cookie_dict[m] = n.valuereq = Request(url='http://dig.chouti.com/login',method='POST',headers={'Content-Type': 'application/x-www-form-urlencoded; charset=UTF-8'},body='phone=8615131255089&password=pppppppp&oneMonth=1',cookies=self.cookie_dict,callback=self.check_login)yield reqdef check_login(self, response):req = Request(url='http://dig.chouti.com/',method='GET',callback=self.show,cookies=self.cookie_dict,dont_filter=True)yield reqdef show(self, response):# print(response)hxs = HtmlXPathSelector(response)news_list = hxs.select('//div[@id="content-list"]/div[@class="item"]')for new in news_list:# temp = new.xpath('div/div[@class="part2"]/@share-linkid').extract()link_id = new.xpath('*/div[@class="part2"]/@share-linkid').extract_first()yield Request(url='http://dig.chouti.com/link/vote?linksId=%s' %(link_id,),method='POST',cookies=self.cookie_dict,callback=self.do_favor)page_list = hxs.select('//div[@id="dig_lcpage"]//a[re:test(@href, "/all/hot/recent/\d+")]/@href').extract()for page in page_list:page_url = 'http://dig.chouti.com%s' % pageimport hashlibhash = hashlib.md5()hash.update(bytes(page_url,encoding='utf-8'))key = hash.hexdigest()if key in self.has_request_set:passelse:self.has_request_set[key] = page_urlyield Request(url=page_url,method='GET',callback=self.show)def do_favor(self, response):print(response.text)

注意：settings.py中设置DEPTH_LIMIT = 1来指定“递归”的层数。

5. 格式化处理

上述实例只是简单的处理，所以在parse方法中直接处理。如果对于想要获取更多的数据处理，则可以利用Scrapy的items将数据格式化，然后统一交由pipelines来处理。

spiders/xiahuar.py

import scrapy
from scrapy.selector import HtmlXPathSelector
from scrapy.http.request import Request
from scrapy.http.cookies import CookieJar
from scrapy import FormRequestclass XiaoHuarSpider(scrapy.Spider):# 爬虫应用的名称，通过此名称启动爬虫命令name = "xiaohuar"# 允许的域名allowed_domains = ["xiaohuar.com"]start_urls = ["http://www.xiaohuar.com/list-1-1.html",]# custom_settings = {#     'ITEM_PIPELINES':{#         'spider1.pipelines.JsonPipeline': 100#     }# }has_request_set = {}def parse(self, response):# 分析页面# 找到页面中符合规则的内容（校花图片），保存# 找到所有的a标签，再访问其他a标签，一层一层的搞下去hxs = HtmlXPathSelector(response)items = hxs.select('//div[@class="item_list infinite_scroll"]/div')for item in items:src = item.select('.//div[@class="img"]/a/img/@src').extract_first()name = item.select('.//div[@class="img"]/span/text()').extract_first()school = item.select('.//div[@class="img"]/div[@class="btns"]/a/text()').extract_first()url = "http://www.xiaohuar.com%s" % srcfrom ..items import XiaoHuarItemobj = XiaoHuarItem(name=name, school=school, url=url)yield objurls = hxs.select('//a[re:test(@href, "http://www.xiaohuar.com/list-1-\d+.html")]/@href')for url in urls:key = self.md5(url)if key in self.has_request_set:passelse:self.has_request_set[key] = urlreq = Request(url=url,method='GET',callback=self.parse)yield req@staticmethoddef md5(val):import hashlibha = hashlib.md5()ha.update(bytes(val, encoding='utf-8'))key = ha.hexdigest()return key

items

import scrapyclass XiaoHuarItem(scrapy.Item):name = scrapy.Field()school = scrapy.Field()url = scrapy.Field()

pipelines

import json
import os
import requestsclass JsonPipeline(object):def __init__(self):self.file = open('xiaohua.txt', 'w')def process_item(self, item, spider):v = json.dumps(dict(item), ensure_ascii=False)self.file.write(v)self.file.write('\n')self.file.flush()return itemclass FilePipeline(object):def __init__(self):if not os.path.exists('imgs'):os.makedirs('imgs')def process_item(self, item, spider):response = requests.get(item['url'], stream=True)file_name = '%s_%s.jpg' % (item['name'], item['school'])with open(os.path.join('imgs', file_name), mode='wb') as f:f.write(response.content)return item

settings

ITEM_PIPELINES = {'spider1.pipelines.JsonPipeline': 100,'spider1.pipelines.FilePipeline': 300,
}
# 每行后面的整型值，确定了他们运行的顺序，item按数字从低到高的顺序，通过pipeline，通常将这些数字定义在0-1000范围内。

自定义pipeline

from scrapy.exceptions import DropItemclass CustomPipeline(object):def __init__(self,v):self.value = vdef process_item(self, item, spider):# 操作并进行持久化# return表示会被后续的pipeline继续处理return item# 表示将item丢弃，不会被后续pipeline处理# raise DropItem()@classmethoddef from_crawler(cls, crawler):"""
        初始化时候，用于创建pipeline对象:param crawler: :return: """
        val = crawler.settings.getint('MMMM')return cls(val)def open_spider(self,spider):"""
        爬虫开始执行时，调用:param spider: :return: """
        print('000000')def close_spider(self,spider):"""
        爬虫关闭时，被调用:param spider: :return: """
        print('111111')

6.中间件

爬虫中间件

class SpiderMiddleware(object):def process_spider_input(self,response, spider):"""
        下载完成，执行，然后交给parse处理:param response: :param spider: :return: """
        passdef process_spider_output(self,response, result, spider):"""
        spider处理完成，返回时调用:param response::param result::param spider::return: 必须返回包含 Request 或 Item 对象的可迭代对象(iterable)"""
        return resultdef process_spider_exception(self,response, exception, spider):"""
        异常调用:param response::param exception::param spider::return: None,继续交给后续中间件处理异常；含 Response 或 Item 的可迭代对象(iterable)，交给调度器或pipeline"""
        return Nonedef process_start_requests(self,start_requests, spider):"""
        爬虫启动时调用:param start_requests::param spider::return: 包含 Request 对象的可迭代对象"""
        return start_requests

下载器中间件

class DownMiddleware1(object):def process_request(self, request, spider):"""
        请求需要被下载时，经过所有下载器中间件的process_request调用:param request: :param spider: :return:  None,继续后续中间件去下载；Response对象，停止process_request的执行，开始执行process_responseRequest对象，停止中间件的执行，将Request重新调度器raise IgnoreRequest异常，停止process_request的执行，开始执行process_exception"""
        passdef process_response(self, request, response, spider):"""
        spider处理完成，返回时调用:param response::param result::param spider::return: Response 对象：转交给其他中间件process_responseRequest 对象：停止中间件，request会被重新调度下载raise IgnoreRequest 异常：调用Request.errback"""
        print('response1')return responsedef process_exception(self, request, exception, spider):"""
        当下载处理器(download handler)或 process_request() (下载中间件)抛出异常:param response::param exception::param spider::return: None：继续交给后续中间件处理异常；Response对象：停止后续process_exception方法Request对象：停止中间件，request将会被重新调用下载"""
        return None

7. 自定制命令

在spiders同级创建任意目录，如：commands
在其中创建 crawlall.py 文件（此处文件名就是自定义的命令）

crawlall.py

from scrapy.commands import ScrapyCommandfrom scrapy.utils.project import get_project_settingsclass Command(ScrapyCommand):requires_project = Truedef syntax(self):return '[options]'def short_desc(self):return 'Runs all of the spiders'def run(self, args, opts):spider_list = self.crawler_process.spiders.list()for name in spider_list:self.crawler_process.crawl(name, **opts.__dict__)self.crawler_process.start()

在settings.py 中添加配置 COMMANDS_MODULE = '项目名称.目录名称'
在项目目录执行命令：scrapy crawlall

8. 自定义扩展

自定义扩展时，利用信号在指定位置注册制定操作

from scrapy import signalsclass MyExtension(object):def __init__(self, value):self.value = value@classmethoddef from_crawler(cls, crawler):val = crawler.settings.getint('MMMM')ext = cls(val)crawler.signals.connect(ext.spider_opened, signal=signals.spider_opened)crawler.signals.connect(ext.spider_closed, signal=signals.spider_closed)return extdef spider_opened(self, spider):print('open')def spider_closed(self, spider):print('close')

9. 避免重复访问

scrapy默认使用 scrapy.dupefilter.RFPDupeFilter 进行去重，相关配置有：

 DUPEFILTER_CLASS = 'scrapy.dupefilter.RFPDupeFilter'
DUPEFILTER_DEBUG = False
JOBDIR = "保存范文记录的日志路径，如：/root/"  # 最终路径为 /root/requests.seen

自定义URL去重操作

class RepeatUrl:def __init__(self):self.visited_url = set()@classmethoddef from_settings(cls, settings):"""
        初始化时，调用:param settings: :return: """
        return cls()def request_seen(self, request):"""
        检测当前请求是否已经被访问过:param request: :return: True表示已经访问过；False表示未访问过"""
        if request.url in self.visited_url:return Trueself.visited_url.add(request.url)return Falsedef open(self):"""
        开始爬去请求时，调用:return: """
        print('open replication')def close(self, reason):"""
        结束爬虫爬取时，调用:param reason: :return: """
        print('close replication')def log(self, request, spider):"""
        记录日志:param request: :param spider: :return: """
        print('repeat', request.url)

10.其他

settings一些设置参数说明：

# -*- coding: utf-8 -*-# Scrapy settings for step8_king project
#
# For simplicity, this file contains only settings considered important or
# commonly used. You can find more settings consulting the documentation:
#
#     http://doc.scrapy.org/en/latest/topics/settings.html
#     http://scrapy.readthedocs.org/en/latest/topics/downloader-middleware.html
#     http://scrapy.readthedocs.org/en/latest/topics/spider-middleware.html

# 1. 爬虫名称
BOT_NAME = 'step8_king'# 2. 爬虫应用路径
SPIDER_MODULES = ['step8_king.spiders']
NEWSPIDER_MODULE = 'step8_king.spiders'# Crawl responsibly by identifying yourself (and your website) on the user-agent
# 3. 客户端 user-agent请求头
# USER_AGENT = 'step8_king (+http://www.yourdomain.com)'# Obey robots.txt rules
# 4. 禁止爬虫配置
# ROBOTSTXT_OBEY = False# Configure maximum concurrent requests performed by Scrapy (default: 16)
# 5. 并发请求数
# CONCURRENT_REQUESTS = 4# Configure a delay for requests for the same website (default: 0)
# See http://scrapy.readthedocs.org/en/latest/topics/settings.html#download-delay
# See also autothrottle settings and docs
# 6. 延迟下载秒数
# DOWNLOAD_DELAY = 2# The download delay setting will honor only one of:
# 7. 单域名访问并发数，并且延迟下次秒数也应用在每个域名
# CONCURRENT_REQUESTS_PER_DOMAIN = 2
# 单IP访问并发数，如果有值则忽略：CONCURRENT_REQUESTS_PER_DOMAIN，并且延迟下次秒数也应用在每个IP
# CONCURRENT_REQUESTS_PER_IP = 3# Disable cookies (enabled by default)
# 8. 是否支持cookie，cookiejar进行操作cookie
# COOKIES_ENABLED = True
# COOKIES_DEBUG = True# Disable Telnet Console (enabled by default)
# 9. Telnet用于查看当前爬虫的信息，操作爬虫等...
#    使用telnet ip port ，然后通过命令操作
# TELNETCONSOLE_ENABLED = True
# TELNETCONSOLE_HOST = '127.0.0.1'
# TELNETCONSOLE_PORT = [6023,]# 10. 默认请求头
# Override the default request headers:
# DEFAULT_REQUEST_HEADERS = {
#     'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8',
#     'Accept-Language': 'en',
# }# Configure item pipelines
# See http://scrapy.readthedocs.org/en/latest/topics/item-pipeline.html
# 11. 定义pipeline处理请求
# ITEM_PIPELINES = {
#    'step8_king.pipelines.JsonPipeline': 700,
#    'step8_king.pipelines.FilePipeline': 500,
# }# 12. 自定义扩展，基于信号进行调用
# Enable or disable extensions
# See http://scrapy.readthedocs.org/en/latest/topics/extensions.html
# EXTENSIONS = {
#     # 'step8_king.extensions.MyExtension': 500,
# }# 13. 爬虫允许的最大深度，可以通过meta查看当前深度；0表示无深度
# DEPTH_LIMIT = 3# 14. 爬取时，0表示深度优先Lifo(默认)；1表示广度优先FiFo# 后进先出，深度优先
# DEPTH_PRIORITY = 0
# SCHEDULER_DISK_QUEUE = 'scrapy.squeue.PickleLifoDiskQueue'
# SCHEDULER_MEMORY_QUEUE = 'scrapy.squeue.LifoMemoryQueue'
# 先进先出，广度优先# DEPTH_PRIORITY = 1
# SCHEDULER_DISK_QUEUE = 'scrapy.squeue.PickleFifoDiskQueue'
# SCHEDULER_MEMORY_QUEUE = 'scrapy.squeue.FifoMemoryQueue'# 15. 调度器队列
# SCHEDULER = 'scrapy.core.scheduler.Scheduler'
# from scrapy.core.scheduler import Scheduler# 16. 访问URL去重
# DUPEFILTER_CLASS = 'step8_king.duplication.RepeatUrl'# Enable and configure the AutoThrottle extension (disabled by default)
# See http://doc.scrapy.org/en/latest/topics/autothrottle.html"""
17. 自动限速算法from scrapy.contrib.throttle import AutoThrottle自动限速设置1. 获取最小延迟 DOWNLOAD_DELAY2. 获取最大延迟 AUTOTHROTTLE_MAX_DELAY3. 设置初始下载延迟 AUTOTHROTTLE_START_DELAY4. 当请求下载完成后，获取其"连接"时间 latency，即：请求连接到接受到响应头之间的时间5. 用于计算的... AUTOTHROTTLE_TARGET_CONCURRENCYtarget_delay = latency / self.target_concurrencynew_delay = (slot.delay + target_delay) / 2.0 # 表示上一次的延迟时间new_delay = max(target_delay, new_delay)new_delay = min(max(self.mindelay, new_delay), self.maxdelay)slot.delay = new_delay
"""

# 开始自动限速
# AUTOTHROTTLE_ENABLED = True
# The initial download delay
# 初始下载延迟
# AUTOTHROTTLE_START_DELAY = 5
# The maximum download delay to be set in case of high latencies
# 最大下载延迟
# AUTOTHROTTLE_MAX_DELAY = 10
# The average number of requests Scrapy should be sending in parallel to each remote server
# 平均每秒并发数
# AUTOTHROTTLE_TARGET_CONCURRENCY = 1.0# Enable showing throttling stats for every response received:
# 是否显示
# AUTOTHROTTLE_DEBUG = True# Enable and configure HTTP caching (disabled by default)
# See http://scrapy.readthedocs.org/en/latest/topics/downloader-middleware.html#httpcache-middleware-settings"""
18. 启用缓存目的用于将已经发送的请求或相应缓存下来，以便以后使用from scrapy.downloadermiddlewares.httpcache import HttpCacheMiddlewarefrom scrapy.extensions.httpcache import DummyPolicyfrom scrapy.extensions.httpcache import FilesystemCacheStorage
"""
# 是否启用缓存策略
# HTTPCACHE_ENABLED = True# 缓存策略：所有请求均缓存，下次在请求直接访问原来的缓存即可
# HTTPCACHE_POLICY = "scrapy.extensions.httpcache.DummyPolicy"
# 缓存策略：根据Http响应头：Cache-Control、Last-Modified 等进行缓存的策略
# HTTPCACHE_POLICY = "scrapy.extensions.httpcache.RFC2616Policy"# 缓存超时时间
# HTTPCACHE_EXPIRATION_SECS = 0# 缓存保存路径
# HTTPCACHE_DIR = 'httpcache'# 缓存忽略的Http状态码
# HTTPCACHE_IGNORE_HTTP_CODES = []# 缓存存储的插件
# HTTPCACHE_STORAGE = 'scrapy.extensions.httpcache.FilesystemCacheStorage'"""
19. 代理，需要在环境变量中设置from scrapy.contrib.downloadermiddleware.httpproxy import HttpProxyMiddleware方式一：使用默认os.environ{http_proxy:http://root:woshiniba@192.168.11.11:9999/https_proxy:http://192.168.11.11:9999/
        }方式二：使用自定义下载中间件def to_bytes(text, encoding=None, errors='strict'):if isinstance(text, bytes):return textif not isinstance(text, six.string_types):raise TypeError('to_bytes must receive a unicode, str or bytes ''object, got %s' % type(text).__name__)if encoding is None:encoding = 'utf-8'return text.encode(encoding, errors)class ProxyMiddleware(object):def process_request(self, request, spider):PROXIES = [{'ip_port': '111.11.228.75:80', 'user_pass': ''},{'ip_port': '120.198.243.22:80', 'user_pass': ''},{'ip_port': '111.8.60.9:8123', 'user_pass': ''},{'ip_port': '101.71.27.120:80', 'user_pass': ''},{'ip_port': '122.96.59.104:80', 'user_pass': ''},{'ip_port': '122.224.249.122:8088', 'user_pass': ''},]proxy = random.choice(PROXIES)if proxy['user_pass'] is not None:request.meta['proxy'] = to_bytes（"http://%s" % proxy['ip_port']）encoded_user_pass = base64.encodestring(to_bytes(proxy['user_pass']))request.headers['Proxy-Authorization'] = to_bytes('Basic ' + encoded_user_pass)print "**************ProxyMiddleware have pass************" + proxy['ip_port']else:print "**************ProxyMiddleware no pass************" + proxy['ip_port']request.meta['proxy'] = to_bytes("http://%s" % proxy['ip_port'])DOWNLOADER_MIDDLEWARES = {'step8_king.middlewares.ProxyMiddleware': 500,}"""

"""
20. Https访问Https访问时有两种情况：1. 要爬取网站使用的可信任证书(默认支持)DOWNLOADER_HTTPCLIENTFACTORY = "scrapy.core.downloader.webclient.ScrapyHTTPClientFactory"DOWNLOADER_CLIENTCONTEXTFACTORY = "scrapy.core.downloader.contextfactory.ScrapyClientContextFactory"2. 要爬取网站使用的自定义证书DOWNLOADER_HTTPCLIENTFACTORY = "scrapy.core.downloader.webclient.ScrapyHTTPClientFactory"DOWNLOADER_CLIENTCONTEXTFACTORY = "step8_king.https.MySSLFactory"# https.pyfrom scrapy.core.downloader.contextfactory import ScrapyClientContextFactoryfrom twisted.internet.ssl import (optionsForClientTLS, CertificateOptions, PrivateCertificate)class MySSLFactory(ScrapyClientContextFactory):def getCertificateOptions(self):from OpenSSL import cryptov1 = crypto.load_privatekey(crypto.FILETYPE_PEM, open('/Users/wupeiqi/client.key.unsecure', mode='r').read())v2 = crypto.load_certificate(crypto.FILETYPE_PEM, open('/Users/wupeiqi/client.pem', mode='r').read())return CertificateOptions(privateKey=v1,  # pKey对象certificate=v2,  # X509对象verify=False,method=getattr(self, 'method', getattr(self, '_ssl_method', None)))其他：相关类scrapy.core.downloader.handlers.http.HttpDownloadHandlerscrapy.core.downloader.webclient.ScrapyHTTPClientFactoryscrapy.core.downloader.contextfactory.ScrapyClientContextFactory相关配置DOWNLOADER_HTTPCLIENTFACTORYDOWNLOADER_CLIENTCONTEXTFACTORY"""
"""
21. 爬虫中间件class SpiderMiddleware(object):def process_spider_input(self,response, spider):'''
            下载完成，执行，然后交给parse处理:param response: :param spider: :return: '''
            passdef process_spider_output(self,response, result, spider):'''
            spider处理完成，返回时调用:param response::param result::param spider::return: 必须返回包含 Request 或 Item 对象的可迭代对象(iterable)'''
            return resultdef process_spider_exception(self,response, exception, spider):'''
            异常调用:param response::param exception::param spider::return: None,继续交给后续中间件处理异常；含 Response 或 Item 的可迭代对象(iterable)，交给调度器或pipeline'''
            return Nonedef process_start_requests(self,start_requests, spider):'''
            爬虫启动时调用:param start_requests::param spider::return: 包含 Request 对象的可迭代对象'''
            return start_requests内置爬虫中间件：'scrapy.contrib.spidermiddleware.httperror.HttpErrorMiddleware': 50,'scrapy.contrib.spidermiddleware.offsite.OffsiteMiddleware': 500,'scrapy.contrib.spidermiddleware.referer.RefererMiddleware': 700,'scrapy.contrib.spidermiddleware.urllength.UrlLengthMiddleware': 800,'scrapy.contrib.spidermiddleware.depth.DepthMiddleware': 900,"""
# from scrapy.contrib.spidermiddleware.referer import RefererMiddleware
# Enable or disable spider middlewares
# See http://scrapy.readthedocs.org/en/latest/topics/spider-middleware.html
SPIDER_MIDDLEWARES = {# 'step8_king.middlewares.SpiderMiddleware': 543,
}"""
22. 下载中间件class DownMiddleware1(object):def process_request(self, request, spider):'''
            请求需要被下载时，经过所有下载器中间件的process_request调用:param request::param spider::return:None,继续后续中间件去下载；Response对象，停止process_request的执行，开始执行process_responseRequest对象，停止中间件的执行，将Request重新调度器raise IgnoreRequest异常，停止process_request的执行，开始执行process_exception'''
            passdef process_response(self, request, response, spider):'''
            spider处理完成，返回时调用:param response::param result::param spider::return:Response 对象：转交给其他中间件process_responseRequest 对象：停止中间件，request会被重新调度下载raise IgnoreRequest 异常：调用Request.errback'''
            print('response1')return responsedef process_exception(self, request, exception, spider):'''
            当下载处理器(download handler)或 process_request() (下载中间件)抛出异常:param response::param exception::param spider::return:None：继续交给后续中间件处理异常；Response对象：停止后续process_exception方法Request对象：停止中间件，request将会被重新调用下载'''
            return None默认下载中间件{'scrapy.contrib.downloadermiddleware.robotstxt.RobotsTxtMiddleware': 100,'scrapy.contrib.downloadermiddleware.httpauth.HttpAuthMiddleware': 300,'scrapy.contrib.downloadermiddleware.downloadtimeout.DownloadTimeoutMiddleware': 350,'scrapy.contrib.downloadermiddleware.useragent.UserAgentMiddleware': 400,'scrapy.contrib.downloadermiddleware.retry.RetryMiddleware': 500,'scrapy.contrib.downloadermiddleware.defaultheaders.DefaultHeadersMiddleware': 550,'scrapy.contrib.downloadermiddleware.redirect.MetaRefreshMiddleware': 580,'scrapy.contrib.downloadermiddleware.httpcompression.HttpCompressionMiddleware': 590,'scrapy.contrib.downloadermiddleware.redirect.RedirectMiddleware': 600,'scrapy.contrib.downloadermiddleware.cookies.CookiesMiddleware': 700,'scrapy.contrib.downloadermiddleware.httpproxy.HttpProxyMiddleware': 750,'scrapy.contrib.downloadermiddleware.chunked.ChunkedTransferMiddleware': 830,'scrapy.contrib.downloadermiddleware.stats.DownloaderStats': 850,'scrapy.contrib.downloadermiddleware.httpcache.HttpCacheMiddleware': 900,}"""
# from scrapy.contrib.downloadermiddleware.httpauth import HttpAuthMiddleware
# Enable or disable downloader middlewares
# See http://scrapy.readthedocs.org/en/latest/topics/downloader-middleware.html
# DOWNLOADER_MIDDLEWARES = {
#    'step8_king.middlewares.DownMiddleware1': 100,
#    'step8_king.middlewares.DownMiddleware2': 500,
# }

11.TinyScrapy

#!/usr/bin/env python
# -*- coding:utf-8 -*-
import types
from twisted.internet import defer
from twisted.web.client import getPage
from twisted.internet import reactorclass Request(object):def __init__(self, url, callback):self.url = urlself.callback = callbackself.priority = 0class HttpResponse(object):def __init__(self, content, request):self.content = contentself.request = requestclass ChouTiSpider(object):def start_requests(self):url_list = ['http://www.cnblogs.com/', 'http://www.bing.com']for url in url_list:yield Request(url=url, callback=self.parse)def parse(self, response):print(response.request.url)# yield Request(url="http://www.baidu.com", callback=self.parse)from queue import Queue
Q = Queue()class CallLaterOnce(object):def __init__(self, func, *a, **kw):self._func = funcself._a = aself._kw = kwself._call = Nonedef schedule(self, delay=0):if self._call is None:self._call = reactor.callLater(delay, self)def cancel(self):if self._call:self._call.cancel()def __call__(self):self._call = Nonereturn self._func(*self._a, **self._kw)class Engine(object):def __init__(self):self.nextcall = Noneself.crawlling = []self.max = 5self._closewait = Nonedef get_response(self,content, request):response = HttpResponse(content, request)gen = request.callback(response)if isinstance(gen, types.GeneratorType):for req in gen:req.priority = request.priority + 1Q.put(req)def rm_crawlling(self,response,d):self.crawlling.remove(d)def _next_request(self,spider):if Q.qsize() == 0 and len(self.crawlling) == 0:self._closewait.callback(None)if len(self.crawlling) >= 5:returnwhile len(self.crawlling) < 5:try:req = Q.get(block=False)except Exception as e:req = Noneif not req:returnd = getPage(req.url.encode('utf-8'))self.crawlling.append(d)d.addCallback(self.get_response, req)d.addCallback(self.rm_crawlling,d)d.addCallback(lambda _: self.nextcall.schedule())@defer.inlineCallbacksdef crawl(self):spider = ChouTiSpider()start_requests = iter(spider.start_requests())flag = Truewhile flag:try:req = next(start_requests)Q.put(req)except StopIteration as e:flag = Falseself.nextcall = CallLaterOnce(self._next_request,spider)self.nextcall.schedule()self._closewait = defer.Deferred()yield self._closewait@defer.inlineCallbacksdef pp(self):yield self.crawl()_active = set()
obj = Engine()
d = obj.crawl()
_active.add(d)li = defer.DeferredList(_active)
li.addBoth(lambda _,*a,**kw: reactor.stop())reactor.run()